{
 "cells": [
  {
   "cell_type": "markdown",
   "source": [
    "# 1 常见图形种类及意义\n",
    "- 折线图：以折线的上升或下降来表示统计数量的增减变化的统计图\n",
    "    - 特点：能够显示数据的变化趋势，反映事物的变化情况。(变化)\n",
    "    - api：plt.plot(x, y)\n",
    "- 散点图：用两组数据构成多个坐标点，考察坐标点的分布,判断两变量之间是否存在某种关联或总结坐标点的分布模式。\n",
    "    - 特点：判断变量之间是否存在数量关联趋势,展示离群点(分布规律)\n",
    "    - api：plt.scatter(x, y)\n",
    "- 柱状图：排列在工作表的列或行中的数据可以绘制到柱状图中。\n",
    "    - 特点：绘制连离散的数据,能够一眼看出各个数据的大小,比较数据之间的差别。(统计/对比)\n",
    "    - api：plt.bar(x, width, align='center', **kwargs)\n",
    "        ```\n",
    "        Parameters:    \n",
    "        x : 需要传递的数据\n",
    "        \n",
    "        width : 柱状图的宽度\n",
    "        \n",
    "        align : 每个柱状图的位置对齐方式\n",
    "            {‘center’, ‘edge’}, optional, default: ‘center’\n",
    "        \n",
    "        **kwargs :\n",
    "        color:选择柱状图的颜色\n",
    "        ```\n",
    "- 直方图：由一系列高度不等的纵向条纹或线段表示数据分布的情况。 一般用横轴表示数据范围，纵轴表示分布情况。\n",
    "    - 特点：绘制连续性的数据展示一组或者多组数据的分布状况(统计)\n",
    "    - api：plt.hist(x, bins=None)\n",
    "        ```\n",
    "        Parameters:    \n",
    "        x : 需要传递的数据\n",
    "        bins : 组数\n",
    "        ```\n",
    "- 饼图：用于表示不同分类的占比情况，通过弧度大小来对比各种分类。\n",
    "    - 特点：分类数据的占比情况(占比)\n",
    "    - api：plt.pie(x, labels=,autopct=,colors)\n",
    "        ```\n",
    "        Parameters:  \n",
    "        x:数量，自动算百分比\n",
    "        labels:每部分名称\n",
    "        autopct:占比显示指定%1.2f%%\n",
    "        colors:每部分颜色\n",
    "        ```\n",
    "# 2 散点图绘制\n",
    "需求：探究房屋面积和房屋价格的关系"
   ],
   "metadata": {
    "collapsed": false
   },
   "id": "61a2f75d584d3298"
  },
  {
   "cell_type": "code",
   "outputs": [
    {
     "data": {
      "text/plain": "<Figure size 2000x800 with 1 Axes>",
      "image/png": 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IAAAAAABQGMIIAAAAAABQGMIIAAAAAABQGMIIAAAAAABQGP8/3qnVCidKG28AAAAASUVORK5CYII="
     },
     "metadata": {},
     "output_type": "display_data"
    }
   ],
   "source": [
    "import matplotlib.pyplot as plt\n",
    "# 0.准备数据\n",
    "# 房屋面积数据：\n",
    "x = [225.98, 247.07, 253.14, 457.85, 241.58, 301.01,  20.67, 288.64,\n",
    "       163.56, 120.06, 207.83, 342.75, 147.9 ,  53.06, 224.72,  29.51,\n",
    "        21.61, 483.21, 245.25, 399.25, 343.35]\n",
    "# 房屋价格数据：\n",
    "y = [196.63, 203.88, 210.75, 372.74, 202.41, 247.61,  24.9 , 239.34,\n",
    "       140.32, 104.15, 176.84, 288.23, 128.79,  49.64, 191.74,  33.1 ,\n",
    "        30.74, 400.02, 205.35, 330.64, 283.45]\n",
    "\n",
    "# 1.创建画布\n",
    "plt.figure(figsize=(20, 8), dpi=100)\n",
    "\n",
    "# 2.绘制散点图\n",
    "plt.scatter(x, y)\n",
    "\n",
    "# 3.显示图像\n",
    "plt.show()"
   ],
   "metadata": {
    "collapsed": false,
    "ExecuteTime": {
     "end_time": "2024-02-20T07:30:45.550991300Z",
     "start_time": "2024-02-20T07:30:45.121870700Z"
    }
   },
   "id": "69098450e800d04c",
   "execution_count": 1
  },
  {
   "cell_type": "markdown",
   "source": [
    "# 3 柱状图绘制\n",
    "需求-对比每部电影的票房收入"
   ],
   "metadata": {
    "collapsed": false
   },
   "id": "5d090a4ac643e0ae"
  },
  {
   "cell_type": "code",
   "outputs": [
    {
     "data": {
      "text/plain": "<Figure size 2000x800 with 1 Axes>",
      "image/png": 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"
     },
     "metadata": {},
     "output_type": "display_data"
    }
   ],
   "source": [
    "import matplotlib.pyplot as plt\n",
    "## 中文显示问题解决\n",
    "from pylab import mpl\n",
    "# 设置显示中文字体\n",
    "mpl.rcParams[\"font.sans-serif\"] = [\"SimHei\"]\n",
    "# 设置正常显示符号\n",
    "mpl.rcParams[\"axes.unicode_minus\"] = False\n",
    "# 画出温度变化图\n",
    "# 0.准备数据\n",
    "# 电影名字\n",
    "movie_name = ['雷神3：诸神黄昏','正义联盟','东方快车谋杀案','寻梦环游记','全球风暴','降魔传','追捕','七十七天','密战','狂兽','其它']\n",
    "# 横坐标\n",
    "x = range(len(movie_name))\n",
    "# 票房数据\n",
    "y = [73853,57767,22354,15969,14839,8725,8716,8318,7916,6764,52222]\n",
    "\n",
    "# 1.创建画布\n",
    "plt.figure(figsize=(20, 8), dpi=100)\n",
    "\n",
    "# 2.绘制柱状图\n",
    "plt.bar(x, y, width=0.5, color=['b','r','g','y','c','m','y','k','c','g','b'])\n",
    "\n",
    "# 2.1 修改x轴的刻度显示\n",
    "plt.xticks(x, movie_name)\n",
    "\n",
    "# 2.2 添加网格显示\n",
    "plt.grid(linestyle=\"--\", alpha=0.5)\n",
    "\n",
    "# 2.3 添加标题\n",
    "plt.title(\"电影票房收入对比\")\n",
    "\n",
    "# 3.显示图像\n",
    "plt.show()"
   ],
   "metadata": {
    "collapsed": false,
    "ExecuteTime": {
     "end_time": "2024-02-20T07:31:57.607112200Z",
     "start_time": "2024-02-20T07:31:57.468106700Z"
    }
   },
   "id": "8628d6afd7f0214d",
   "execution_count": 4
  },
  {
   "cell_type": "markdown",
   "source": [
    "# 4 小结\n",
    "- 折线图【知道】\n",
    "    - 能够显示数据的变化趋势，反映事物的变化情况。(变化)\n",
    "    - plt.plot()\n",
    "- 散点图【知道】\n",
    "    - 判断变量之间是否存在数量关联趋势,展示离群点(分布规律)\n",
    "    - plt.scatter()\n",
    "- 柱状图【知道】\n",
    "    - 绘制连离散的数据,能够一眼看出各个数据的大小,比较数据之间的差别。(统计/对比)\n",
    "    - plt.bar(x, width, align=\"center\")\n",
    "- 直方图【知道】\n",
    "    - 绘制连续性的数据展示一组或者多组数据的分布状况(统计)\n",
    "    - plt.hist(x, bins)\n",
    "- 饼图【知道】\n",
    "    - 用于表示不同分类的占比情况，通过弧度大小来对比各种分类\n",
    "    - plt.pie(x, labels, autopct, colors)"
   ],
   "metadata": {
    "collapsed": false
   },
   "id": "55382082dcd73846"
  }
 ],
 "metadata": {
  "kernelspec": {
   "display_name": "Python 3",
   "language": "python",
   "name": "python3"
  },
  "language_info": {
   "codemirror_mode": {
    "name": "ipython",
    "version": 2
   },
   "file_extension": ".py",
   "mimetype": "text/x-python",
   "name": "python",
   "nbconvert_exporter": "python",
   "pygments_lexer": "ipython2",
   "version": "2.7.6"
  }
 },
 "nbformat": 4,
 "nbformat_minor": 5
}
